Build an AI Document (PDF, DOC, XML) Processing Pipeline for RAG | Docling, OCR, Chunking, Images

Full-text tutorial with source code (requires MLExpert Pro): https://www.mlexpert.io/v2-bootcamp/document-processing-for-ai Step-by-step tutorial on building an AI document processing pipeline - completely local. Convert PDFs, perform OCR, use VLMs for images, apply LLM semantic chunking, and add context. Get your documents ready for RAG and AI models. Docling: https://docling-project.github.io/docling/ Chunking evaluation: https://research.trychroma.com/evaluating-chunking PDF document: https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-fourth-quarter-and-fiscal-2025 AI Bootcamp: https://www.mlexpert.io/ LinkedIn: https://www.linkedin.com/in/venelin-valkov/ Follow me on X: https://twitter.com/venelin_valkov Discord: https://discord.gg/UaNPxVD6tv Subscribe: http://bit.ly/venelin-subscribe GitHub repository: https://github.com/curiousily/AI-Bootcamp 👍 Don't Forget to Like, Comment, and Subscribe for More Tutorials! 00:00 - Welcome 01:01 - Document processing pipeline 02:07 - Full-text tutorial and source code on MLExpert.io 02:41 - Docling 03:53 - PDF document sample 04:38 - Notebook setup 05:45 - PDF to Markdown (OCR, layout analysis, image to text) 08:45 - Visual inspection 11:02 - Image annotations 14:37 - Chunking with Ollama (and Gemma 3) 19:58 - Contextual enrichment (retrieval) 21:50 - Test the pipeline with simple RAG 24:42 - Conclusion Join this channel to get access to the perks and support my work: https://www.youtube.com/channel/UCoW_WzQNJVAjxo4osNAxd_g/join #rag #ocr #documentprocessing #ollama #chatgpt #python #artificialintelligence